numpy.ma.ndenumerate#

ma.ndenumerate(a, compressed=True)[source]#

Multidimensional index iterator.

Return an iterator yielding pairs of array coordinates and values, skipping elements that are masked. With compressed=False, `ma.masked` is yielded as the value of masked elements. This behavior differs from that of `numpy.ndenumerate`, which yields the value of the underlying data array.

Parameters:
aarray_like

An array with (possibly) masked elements.

compressedbool, optional

If True (default), masked elements are skipped.

`numpy.ndenumerate`

Equivalent function ignoring any mask.

Notes

New in version 1.23.0.

Examples

```>>> import numpy as np
>>> a = np.ma.arange(9).reshape((3, 3))
>>> a[1, 0] = np.ma.masked
>>> a[1, 2] = np.ma.masked
>>> a[2, 1] = np.ma.masked
>>> a
data=[[0, 1, 2],
[--, 4, --],
[6, --, 8]],
[ True, False,  True],
[False,  True, False]],
fill_value=999999)
>>> for index, x in np.ma.ndenumerate(a):
...     print(index, x)
(0, 0) 0
(0, 1) 1
(0, 2) 2
(1, 1) 4
(2, 0) 6
(2, 2) 8
```
```>>> for index, x in np.ma.ndenumerate(a, compressed=False):
...     print(index, x)
(0, 0) 0
(0, 1) 1
(0, 2) 2
(1, 0) --
(1, 1) 4
(1, 2) --
(2, 0) 6
(2, 1) --
(2, 2) 8
```